Read twitter db.ipynb

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  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "import re\n",
      "import json\n",
      "import sqlite3\n",
      "from datetime import datetime \n",
      "import time\n",
      "\n",
      "import goslate\n",
      "gs = goslate.Goslate()\n",
      "\n",
      "\n",
      "\n",
      "litecon = lite.connect('data/BMCbioSample.db')\n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "evolBioCon = sqlite3.connect(\"data/BMCevolBioSample.db\")\n",
      "bioCon = sqlite3.connect(\"data/BMCbioSample.db\")\n",
      "BMCcon = sqlite3.connect(\"data/bmcTwitter.db\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "with BMCcon:\n",
      "    with evolBioCon:\n",
      "        litecur = evolBioCon.cursor()\n",
      "        litecur.execute(\"SELECT * FROM sample\")\n",
      "\t# this will be big-ish in memory but shouldn't be a major issue, the whole SQLite db is about 60mb after one full run.\n",
      "\tjournals = litecur.fetchall()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.read_sql(\"SELECT doi, tweet_id, old_screen_name, tweet FROM sample WHERE tweet IS NOT NULL \", BMCcon, index_col='tweet_id')\n",
      "df['tweet'] = df.tweet.apply(lambda x: json.loads(x) if x is not None else None)\n",
      "\n",
      "df['created_at'] = df.tweet.apply(lambda x: time.strftime('%Y-%m-%d %H:%M:%S', time.strptime(x['created_at'],'%a %b %d %H:%M:%S +0000 %Y')))\n",
      "df['created_at_dayofweek'] = df.tweet.apply(lambda x: x['created_at'][0:3])\n",
      "df['screen_name'] = df.tweet.apply(lambda x: x['user']['screen_name'])\n",
      "df['user_id_str'] = df.tweet.apply(lambda x: x['user']['id_str'])\n",
      "df['user_utc_offset'] = df.tweet.apply(lambda x: x['user']['utc_offset'])\n",
      "df['user_followers_count'] = df.tweet.apply(lambda x: x['user']['followers_count'])\n",
      "df['user_friends_count'] = df.tweet.apply(lambda x: x['user']['friends_count'])\n",
      "df['user_description'] = df.tweet.apply(lambda x: re.sub( '\\s+', ' ', x['user']['description']).strip())\n",
      "df['is_retweet'] = df.tweet.apply(lambda x: 'retweeted_status' in x)\n",
      "df['retweet_of_status_id_str'] = df.tweet.apply(lambda x: x['retweeted_status']['id_str'] if 'retweeted_status' in x else None)\n",
      "df['retweet_of_screen_name'] = df.tweet.apply(lambda x: x['retweeted_status']['user']['screen_name'] if 'retweeted_status' in x else None)\n",
      "df['is_reply'] = df.tweet.apply(lambda x: x['in_reply_to_status_id'] != None)\n",
      "df['in_reply_to_status_id_str'] = df.tweet.apply(lambda x: x['in_reply_to_status_id_str'])\n",
      "df['in_reply_to_screen_name'] = df.tweet.apply(lambda x: x['in_reply_to_screen_name'])\n",
      "df['text'] = df.tweet.apply(lambda x: re.sub( '\\s+', ' ', x['text']).strip()) # remove commas for CSV simplicity\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.read_sql(\"SELECT doi, tweet_id, old_screen_name, tweet FROM sample WHERE tweet IS NOT NULL \", litecon, index_col='tweet_id')\n",
      "df['tweet'] = df.tweet.apply(lambda x: json.loads(x) if x is not None else None)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "tweet_id\n",
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        "608997839306252288    {u'contributors': None, u'truncated': False, u...\n",
        "Name: tweet, dtype: object"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "try:\n",
      "    del df['tweet']\n",
      "except:\n",
      "    pass\n",
      "df.to_csv('data/BMCBioTweetDetails.csv', encoding='utf8')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.read_sql(\"SELECT tweet_id, tweet FROM sample WHERE tweet IS NOT NULL \", litecon, index_col='tweet_id')\n",
      "df['tweet'] = df.tweet.apply(lambda x: json.loads(x) if x is not None else None)\n",
      "df['screen_name'] = df.tweet.apply(lambda x: x['user']['screen_name'])\n",
      "df['user_description'] = df.tweet.apply(lambda x: re.sub( '\\s+', ' ', x['user']['description']).strip())\n",
      "df['user_followers_count'] = df.tweet.apply(lambda x: x['user']['followers_count'])\n",
      "df['user_friends_count'] = df.tweet.apply(lambda x: x['user']['friends_count'])\n",
      "df.set_index('screen_name', inplace=True)\n",
      "# df['user_description_english'] = df.user_description.map(lambda x: x if all(ord(c) < 128 for c in x) else gs.translate(x, 'en'))\n",
      "try:\n",
      "    del df['tweet']\n",
      "    del df['tweet_id']\n",
      "except:\n",
      "    pass\n",
      "df.drop_duplicates()\n",
      "df.to_csv('data/BMCevolBioUserDetails.txt', encoding='utf8', sep='\\t')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.ix['Mycorampage']['user_description']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df[df['screen_name'] == 'HomareZuki']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>doi</th>\n",
        "      <th>tweet</th>\n",
        "      <th>created_at</th>\n",
        "      <th>created_at_dayofweek</th>\n",
        "      <th>screen_name</th>\n",
        "      <th>user_id_str</th>\n",
        "      <th>user_utc_offset</th>\n",
        "      <th>user_followers_count</th>\n",
        "      <th>user_friends_count</th>\n",
        "      <th>user_description</th>\n",
        "      <th>is_retweet</th>\n",
        "      <th>retweet_of_status_id_str</th>\n",
        "      <th>retweet_of_screen_name</th>\n",
        "      <th>is_reply</th>\n",
        "      <th>in_reply_to_status_id_str</th>\n",
        "      <th>in_reply_to_screen_name</th>\n",
        "      <th>text</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>tweet_id</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>537918381341417473</th>\n",
        "      <td>10.1186/preaccept-2055025475136453</td>\n",
        "      <td>{u'contributors': None, u'truncated': False, u...</td>\n",
        "      <td>2014-11-27 10:38:30</td>\n",
        "      <td>Thu</td>\n",
        "      <td>HomareZuki</td>\n",
        "      <td>267046963</td>\n",
        "      <td>-36000.0</td>\n",
        "      <td>170</td>\n",
        "      <td>139</td>\n",
        "      <td></td>\n",
        "      <td>False</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>False</td>\n",
        "      <td>None</td>\n",
        "      <td>None</td>\n",
        "      <td>\u300e\u8449\u3063\u3071\u306b\u305d\u3063\u304f\u308a\u306a\uff08\u64ec\u614b\u3057\u305f\uff09\u8776\u306e\u6a21\u69d8\u306f\u3069\u306e\u3088\u3046\u306b\u9032\u5316\u3057\u3066\u304d\u305f\u306e\u304b\uff1f\u300f\u3092\u660e\u3089\u304b\u306b\u3057\u305f\u8ad6\u6587\u304c...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "                                                   doi  \\\n",
        "tweet_id                                                 \n",
        "537918381341417473  10.1186/preaccept-2055025475136453   \n",
        "\n",
        "                                                                tweet  \\\n",
        "tweet_id                                                                \n",
        "537918381341417473  {u'contributors': None, u'truncated': False, u...   \n",
        "\n",
        "                             created_at created_at_dayofweek screen_name  \\\n",
        "tweet_id                                                                   \n",
        "537918381341417473  2014-11-27 10:38:30                  Thu  HomareZuki   \n",
        "\n",
        "                   user_id_str  user_utc_offset  user_followers_count  \\\n",
        "tweet_id                                                                \n",
        "537918381341417473   267046963         -36000.0                   170   \n",
        "\n",
        "                    user_friends_count user_description is_retweet  \\\n",
        "tweet_id                                                             \n",
        "537918381341417473                 139                       False   \n",
        "\n",
        "                   retweet_of_status_id_str retweet_of_screen_name is_reply  \\\n",
        "tweet_id                                                                      \n",
        "537918381341417473                     None                   None    False   \n",
        "\n",
        "                   in_reply_to_status_id_str in_reply_to_screen_name  \\\n",
        "tweet_id                                                               \n",
        "537918381341417473                      None                    None   \n",
        "\n",
        "                                                                 text  \n",
        "tweet_id                                                               \n",
        "537918381341417473  \u300e\u8449\u3063\u3071\u306b\u305d\u3063\u304f\u308a\u306a\uff08\u64ec\u614b\u3057\u305f\uff09\u8776\u306e\u6a21\u69d8\u306f\u3069\u306e\u3088\u3046\u306b\u9032\u5316\u3057\u3066\u304d\u305f\u306e\u304b\uff1f\u300f\u3092\u660e\u3089\u304b\u306b\u3057\u305f\u8ad6\u6587\u304c...  "
       ]
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     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "biodf = pd.read_csv('data/evolBioAllFollowers.csv', header=None )\n",
      "biodf.columns = ['source', 'target', 'doi']\n",
      "biodf['source'] = biodf.source.astype('str')\n",
      "biodf['target'] = biodf.target.astype('str')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 48
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "m = 0\n",
      "print 'original: ', len(set(df[df.retweet_of_status_id_str == '537918381341417473'].user_id_str).intersection(biodf[biodf.source == '267046963'].target))\n",
      "for orig_follower in biodf[biodf.source == '267046963'].target:\n",
      "    n = len(set(df[df.retweet_of_status_id_str == '537918381341417473'].user_id_str).intersection(biodf[biodf.source == orig_follower].target))\n",
      "    if n > 0:\n",
      "        print orig_follower, n\n",
      "    m += n\n",
      "    \n",
      "print m"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "original:  15\n",
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     "prompt_number": 57
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    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(set(df[df.retweet_of_status_id_str == '537918381341417473'].user_id_str).intersection()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
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        "15"
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     ],
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    {
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     "collapsed": false,
     "input": [
      "biodf[['source', 'target']"
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     "language": "python",
     "metadata": {},
     "outputs": [
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        "             source              target\n",
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        "...             ...                 ...\n",
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        "\n",
        "[186911 rows x 2 columns]"
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 ]
}